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人間科学研究 Vol. 29, Supplement（2016）
修士論文要旨
Development of a process-based model forced by simple climate variables for estimating primary productivity
渥美 和幸（Kazuyuki Atsumi） 指導：太田 俊二
1. Introduction
Climate change affects primary productivity on which heterotrophs in terrestrial ecosystems depend. Hence, evaluating primary productivity based on climate conditions is necessary. Various types of models to estimate primary productivity have been developed, resulting in growing understanding about the roles of terrestrial ecosystems in material circulations and energy flows. However, few have good predictability and utility because current approaches used for quantifying primary productivity are excessively simple or complex. Although empirical models based on statistical relationships are easily applied because of their simple structures, their results for future projection are undesirable. On the contrary, mechanistic models are coupled to global circulation models; hence, they require vast amounts of computing power. To overcome these limitations, a process-based model with intermediate complexity and a broad range of utility must be developed. Therefore, this study presents a new climate-driven model suited for estimating productivity (CMSEP) that uses simple meteorological variables.
2. Model Descriptions
CMSEP consists of four submodules: (1) energy and water balance, (2) water-carbon exchange, (3) allocation o f a s s i m i l a t e d c a r b o n , a n d (4) p h e n o l o g y . Photosynthesis and evapotranspiration rates are computed at a 30-min interval in (1) and (2) forced by simple meteorological variables (i.e. air temperature, solar radiation, precipitation, relative humidity, and wind speed). The computed primary productivity is then transmitted to (3) and (4) wherein leaf growth is calculated at a one-day interval. Leaf growth is computed based on meteorological resources and allocations of assimilated carbon. The proposed model considers the differences in biophysical and ecophysiological traits among plant functional types (PFTs). Soil water characteristics data and a presumed PFT out of the four are required for this model.
3. Experiment
First, CMSEP was validated by using data observed at 18 representative sites distributed in various climate conditions, and observation data was retrieved from the FLUXNET database. The sites were selected where
gross primary productivity (GPP) data is available. The computed values of evapotranspiration (ET) and leaf area index (LAI) as well as those of GPP were also compared to those measured in order to verify biophysical and ecophysiological processes described in this model. The comparisons of temporal changes in those values were conducted for different time intervals (from 30-min to c.a. 10-day).
Second, spatial distributions of plant productivity and ET in Monsoon Asia were estimated forced by reanalysis climate data. Before running the model, climate and soil data were interpolated to the spatial resolution of vegetation and land use data.
4. Results and Discussion
CMSEP generally reproduced not only the temporal variation in GPP but also those in ET and LAI. In particular, the calculated patterns of seasonal changes in GPP, ET and LAI were compared with those measured for most of the sites. These results suggest that this model, which is forced by simple climate variables, estimates GPP reasonably based on biophysical and ecophysiological processes. Moreover, the annual GPP and ET derived in the model were in accord with observations for every PFT. These results demonstrate that CMSEP is capable of estimating plant productivity reflected in a variety of climates and PFTs.
At some sites, however, GPP and LAI were overestimated (underestimated) owing to weak (strong) responses of leaves to water stress in the model. This suggests that the leaf phenology parameterizations in response to dry stress and the method of PFT classification should be improved.
Spatial distributions of primary productivity and ET were generally compared with previous studies. In cases when the given PFT was not reasonable or the climate data that was not appropriate for this model, however, the primary productivity was overestimated. As a result, the total annual primary productivity in Monsoon Asia was overestimated in contrast to the previous estimates whereas the degree of the overestimation varied for input climate and vegetation data. To estimate accurate primary productivity using CMSEP, developing an appropriate climate and vegetation data set is necessary.
